Towards Auto-Generated Data Systems-Reference-Cited by-同舟云学术

Towards Auto-Generated Data Systems

Published:2023-08 Issue:12 Volume:16 Page:4116-4129
ISSN:2150-8097
Container-title:Proceedings of the VLDB Endowment
language:en
Short-container-title:Proc. VLDB Endow.

Author:

Cheung Alvin¹,Ahmad Maaz Bin Safeer²,Haynes Brandon³,Kittivorawong Chanwut¹,Laddad Shadaj¹,Liu Xiaoxuan¹,Wang Chenglong³,Yan Cong³

Affiliation:

1. University of California, Berkeley

2. Adobe Research

3. Microsoft Research

Abstract

After decades of progress, database management systems (DBMSs) are now the backbones of many data applications that we interact with on a daily basis. Yet, with the emergence of new data types and hardware, building and optimizing new data systems remain as difficult as the heyday of relational databases. In this paper, we summarize our work towards automating the building and optimization of data systems. Drawing from our own experience, we further argue that any automation technique must address three aspects: user specification, code generation, and result validation. We conclude by discussing a case study using videos data processing, along with opportunities for future research towards designing data systems that are automatically generated.

Publisher

Association for Computing Machinery (ACM)

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

Link

https://dl.acm.org/doi/pdf/10.14778/3611540.3611635

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